UMD entomologist helps bring the world’s ant diversity to life in 3D imagery
Researchers leveraged advanced technologies and artificial intelligence to hasten the process of generating 2,000 3D digital ant images. Now, a class of UMD computer science majors is working to bring the data to life.
image:
A 3D model of a soldier ant, showing its morphology in very high detail. Portions of its exoskeleton have been digitally removed, revealing high-resolution renderings of its muscles, nervous system, gastrointestinal tract, and stinger apparatus.
view moreCredit: Credit: Thomas van de Kamp
For more than a decade, Evan Economo’s lab has been using micro-CT machines to scan insect specimens. The resulting X-ray images help researchers study the form and structure of insects—a subfield of entomology known as morphology—but the process is costly and time-consuming.
“One limitation is that you can get this rich 3D dataset, but it could take 10 hours to scan one specimen,” explained Economo, who chairs the University of Maryland’s Department of Entomology and holds the James B. Gahan and Margaret H. Gahan Professorship.
As a senior author of a paper published in the journal Nature Methods on March 5, 2026, Economo tested a high-tech workflow to speed up their efforts. A research team co-led by Economo and Thomas van de Kamp at the Karlsruhe Institute of Technology (KIT) in Germany combined a Synchrotron particle accelerator, X-ray scanning, robotics, and artificial intelligence (AI) to create interactive digital images representing 800 different ant species.
Ultimately, these technologies enabled the team to drastically reduce the time it takes to scan specimens and transform raw image files into high-resolution 3D models.
“We’ve estimated that if we were to carry out this project with a lab-based CT scanner, it would take six years of continuous operation,” said Julian Katzke, the study’s first author and graduate of Economo’s lab at the Okinawa Institute of Science and Technology (OIST) in Japan. “With the setup at KIT, we scanned 2,000 specimens in a single week.”
Dubbed Antscan, this project could serve as a blueprint for future digitization efforts—not just for ants, but for a wide variety of species. The raw files for constructing 3D models are free for anyone to download, and a built-in viewer of every ant allows for easy access to the finished 3D images.
“The value of this study is not only about ants—it's much broader,” said Economo, who is now an adjunct professor at OIST in addition to his UMD role. “When specimens are digitized, we can build libraries of organisms that can streamline their use from scientific laboratories to classrooms to Hollywood studios.”
‘A living library’
To build such an expansive digital library, the research team sourced ethanol-preserved ant specimens from partner institutions, museum collections and experts around the world. After the researchers sorted the specimens by species and caste, they brought them to KIT for high-throughput X-ray micro-CT scanning, which is comparable to medical CT scans but in much higher magnification.
A synchrotron particle accelerator produced a high-intensity X-ray beam to rapidly scan a huge number of specimens, and a robotic sample changer rotated and swapped out the specimens every 30 seconds. This enabled the creation of 2D image stacks that could then be used to construct 3D models.
While useful, the raw image files depicted ant specimens in contorted poses—a far cry from the lifelike models that researchers hoped to build. As a follow-up to Antscan, students in UMD Computer Science Associate Professor James Purtilo’s CMSC 435: “Software Engineering” course are using AI to automate the process of “pose estimation,” enabling awkward ant poses to be transformed into natural ones that might be seen in the wild.
“This collaboration was a great opportunity for us,” Purtilo said. “A capstone is intended to challenge students to integrate skills, function as an effective team and demonstrate their ability to solve real problems. And this problem was a doozy.”
Antscan’s 3D images reveal internal structures like muscles, nervous systems, digestive systems and stingers at micrometer resolution. The models can easily be animated or incorporated into virtual reality worlds for research, education or entertainment.
“To do this manually would have taken years, so without these computational tools it basically would never have been done,” Economo said. “Now, we are making large strides toward creating a living library of interactive models corresponding to Earth’s biodiversity. AI will enable us to explore the diversity of life and share it with the world.”
Antscan in action
The database has already begun to demonstrate its scientific value. Economo was the senior author of a paper published in the journal Science Advances on December 19, 2025, in which researchers used Antscan data to explore whether ant colonies would fare better with a higher number of weaker workers or fewer, more robust workers.
Economo and collaborators studied the correlation between cuticle volume, colony size and colony diversification across more than 500 ant species. The cuticle, which forms the protective outer layer of the exoskeleton, is nutritionally expensive in nitrogen and various minerals, meaning that thicker armor requires a greater investment of resources per ant.
The team found a strong negative correlation between cuticle volume and colony size, suggesting that prioritizing the quantity of ants over the quality of their armor facilitates the development of larger and more diverse ant societies.
In this case, Antscan enabled researchers to take a closer look at cuticle volume, which has been difficult to measure prior to these models. The Antscan project also covered the same ant species as a June 2025 study in the journal Cell, co-authored by Economo, that produced a set of high-quality ant genomes. Combined, these studies could enable more complex research into the relationship between morphological data and genomic variation.
Given their high fidelity, the scans could someday even be used to train machine learning models to accurately detect ants in the field for observational studies of their behavior. Going forward, Economo plans to scan more specimens into the system while continuing to work with UMD computer science students to apply these AI techniques to new datasets.
“This work moves us further into the big data era of capturing, analyzing and sharing organismal shape and form,” Economo said. “The potential for integrating these data with other data types and technologies is immense and very exciting.”
###
Their paper, “High-throughput phenomics of global ant biodiversity,” was published in the journal Nature Methods on March 5, 2026.
This article was adapted from text provided by the Okinawa Institute of Science and Technology.
This research was supported by the German Ministry for Research and Education; the Ministry of Science, Research and the Arts Baden-Württemberg; the German Research Foundation (Grant Nos. INST 35/1503-1 FUGG and 502787686); the Okinawa Institute of Science and Technology Graduate University; the Japan Society for the Promotion of Science (Grant Nos. 18K14768, 21K06326 and 22KJ3077); the Australian Research Council (Award No. IC 180100008); HUN-REN Hungarian Research and the National Research, Development, and Innovation Fund (Grant No. K 147781); the Conselho Nacional de Desenvolvimento Científico e Tecnológico (Grant No. 301495/2019-0); the Critical Ecosystem Partnership Fund, a joint initiative of l’Agence Française de Développement, Conservation International, the European Union, the Global Environment Facility, the government of Japan and the World Bank; the U.S. National Science Foundation (Grant Nos. DEB-1932467, DEB 1927161 and IOS-2128304); the Italian Ministry for University and Research; the Environment and Conservation Fund in Hong Kong (Award No. Nb. ECF 137/2020); and Fundação para a Ciência e a Tecnologia. This article does not necessarily reflect the views of these organizations.
Journal
Nature Methods
Method of Research
Imaging analysis
Subject of Research
Animals
Article Title
High-throughput phenomics of global ant biodiversity
Article Publication Date
5-Mar-2026
Reconstructing the world’s ant diversity in 3D
Antscan provides open access to high-resolution micro-CT scans of 800 different ant species and a revolutionary blueprint for large-scale digitization of small organisms.
image:
A 3D model of a soldier ant, showing its morphology in very high detail. Portions of its exoskeleton have been digitally removed, revealing high-resolution renderings of its muscles, nervous system, gastrointestinal tract, and stinger apparatus.
view moreCredit: Thomas van de Kamp
The shape of an organism is the first way we experience most species and the subject of one of the oldest pursuits in biology. However, the application of big data and computational methods for studying organismal shape has been held back by key technical bottlenecks, making it difficult to capture and share accurate 3D morphological data on large scales.
Now, researchers have broken this bottleneck with a project on ants, small but critical organisms in many ecosystems around the world. Using modern technology, researchers have generated and released a giant and freely available database of over 2000 3D ant models. The project, Antscan, used high-throughput X-ray micro-CT scanning (similar to medical CT scans but in much higher magnification) powered by a synchrotron particle accelerator to rapidly scan a huge number of specimens. These 3D images don’t merely show the exterior exoskeleton of the ants, but also reveal their internal structures like muscles, nervous system, digestive system, and stingers at micrometer resolution. The interdisciplinary work is the culmination of a long project co-led by researchers at the Okinawa Institute of Science and Technology (OIST) in Japan and the Karlsruhe Institute of Technology (KIT) in Germany and involving numerous collaborators from around the world. A new paper in Nature Methods presents both the data and the workflow used to acquire it, providing a blueprint for future large-scale quantification projects.
“This work moves us further into the big data era of capturing, analyzing, and sharing organismal shape and form,” says Professor Evan Economo of the Biodiversity and Biocomplexity Unit at OIST. Antscan adds to the growing collection of major resources on ants tied to OIST, including comprehensive data on the spread of all ant species published in 2022 and high-quality genomes covering most ant genera published last year. And in a recent Science Advances study, the researchers used Antscan data to investigate the fundamental balance of quantity versus quality in organizing ant colonies, finding strong proof that prioritizing the nutritionally cheap ants over more heavily armored and ‘expensive’ ants facilitates the development of larger, more sophisticated, and more resilient ant societies. “The potential for integrating this data is immense and very exciting,” says Economo.
An open library of life
The computational study of morphology, especially in small-sized, diverse groups like ants, has been hindered by the very complexity it aims to capture. Ant specimens are typically collected by hand, but while the traditional method of drying and mounting them preserves their rigid, external exoskeletons, their internal organs deteriorate over time. Another major challenge is size. Many species are barely visible to the naked eye, and accurately quantifying their morphology in 3D requires sophisticated microscopy like micro-CT scans. But because CT scans are both time-consuming and expensive, many species have been excluded from detailed analysis. “If we were to carry out this project with a lab-based CT scanner, it would take around six years of continuous operation. With our setup, we scanned 2000 specimens in a single week,” says first author and OIST graduate Dr. Julian Katzke.
Antscan is the product of close collaboration between OIST, KIT, and the global community of ant researchers. “At times, this work involved our entire lab — we sat for two weeks straight sorting each ant by hand after a full month of cataloging,” recalls Katzke. OIST facilitated the collection of ethanol-preserved ants from countless partner institutions, museum collections, and experts around the world, sorted them all by species and caste, and standardized the metadata, ensuring accurate and fair labelling of each specimen, including who collected the ant, where, and when. Standardized trays of vials with individual ants were then transported to KIT for imaging in their high-throughput synchrotron micro-CT facility. Here, a particle accelerator producing a high-intensity X-ray beam combined with a robot arm for automatically swapping vials produced 3000 negative 2D images of each individual ant, which were then reconstructed into a 3D model, or tomogram.
A key feature of Antscan is its accessibility. All raw files are freely available for anyone to download, and the portal features a built-in viewer for each ant, enabling easy online access to the 3D models. “One of our goals was to democratize access to high-resolution micro-CT scans, which can be prohibitively expensive, especially for smaller institutions or non-institutional experts like citizen scientists, local collectors, or artists and educators,” says Katzke. With the ants’ exoskeleton and musculature captured in high resolution, scientists and artists alike can better model ant movement, both to study locomotion and to create more realistic depictions in multimedia. Katzke concludes: “To me, that’s the most exciting part of the project: opening up the database to a potentially infinite variety of perspectives. I’m thrilled to see how other people will use this data in ways that I couldn’t have imagined.”
Journal
Nature Methods
Method of Research
Imaging analysis
Subject of Research
Animals
Article Title
High-throughput phenomics of global ant biodiversity
Article Publication Date
5-Mar-2026
Example renderings based on data from the Antscan database, here showing an army ant (Eciton hamatum) sub-soldier. (a) shows the full ant, painted with realistic coloring. (b) shows a cross-section of the internal structures, revealing how much of the internal space is occupied by muscles (red). (c) shows the same cross-section, but with muscles removed, revealing the digestive tract (green) and nervous system (blue). (d-f) show zoomed-in renderings of the brain, gut, and sting apparatus.
Credit
Katzke et al., 2026
Four Okinawan ants reproduced from Antscan data: Odontomachus kuroiwae (large left), Diacamma cf. indicum (large right), Pristomyrmex punctatus (small left), Technomyrmex brunneus (small right). Diacamma is shown with a portion of its exoskeleton removed, revealing internal organs like part of its nervous system (blue) and muscle fibers (red). The Pristomyrmex and Diacamma specimens were collected by Professor Kazuki Tsuji from the University of the Ryukyus. The other specimens were collected by the OIST OKEON Project’s field team.
Credit
Julian Katzke
The ant tree of life, with lines indicating their presence in the Antscan dataset. Being open, the database will continue to grow to include the missing species as more scans are obtained.
Credit
Katzke et al., 2026
An example of research using the Antscan database. A large-scale screening of the datasets revealed that biomineral armor, which was previously only found in one species of leaf-cutter ants, was present in a host of fungus-growing ant species. A simple computational trait recognition algorithm was used to detect the thin, white outlines of exoskeletons (seen on the right), which indicate a highly reflective material — minerals. These findings could lead to further insights into the emergence of biomineral armor and its evolution across species.
Credit
Katzke et al., 2026
